Vision Transformers for Breast Cancer Histology Image Classification
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51026-7_2
Reference18 articles.
1. Alotaibi, A., et al.: Vit-deit: an ensemble model for breast cancer histopathological images classification. In: 2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC), pp. 1–6. IEEE (2023)
2. Aresta, G., et al.: Bach: grand challenge on breast cancer histology images. Med. Image Anal. 56, 122–139 (2019)
3. Dosovitskiy, A., et al.: An image is worth 16x16 words: transformers for image recognition at scale (2021). https://doi.org/10.48550/arXiv.2010.11929
4. Gardezi, S.J.S., Elazab, A., Lei, B., Wang, T.: Breast cancer detection and diagnosis using mammographic data: Systematic review. J. Med. Internet Res. 21(7), e14464 (2019)
5. Guo, M.H., et al.: Attention mechanisms in computer vision: a survey. Comput. Vis. Media 8(3), 331–368 (2022)
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